RU2705052C2 - Bit allocation, audio encoding and decoding - Google Patents

Abstract

FIELD: data processing.

SUBSTANCE: invention relates to bits allocation means. Number of bits for each of the plurality of sub-bands in the input spectrum frame in the form of fractions is estimated based on the allowable number of bits for the frame. Redistributed estimated number of bits in at least one sub-band, having number of bits greater than zero, until total number of bits for frame becomes equal to allowable number of bits for frame. Number of distributed bits for the sub-bands is equal to or greater than the predetermined minimum number of bits required for the sub-bands. Input spectrum has at least one of audio characteristics and speech characteristics.

EFFECT: high efficiency of bit allocation.

7 cl, 20 dwg

Description

Technical field

Devices, devices and products in accordance with the present invention relate to encoding and decoding of audio and, in particular, to a method and apparatus for efficiently distributing bits in a frequency domain important for perception, based on subbands, of an audio encoding method and apparatus, method and apparatus decoding audio, recording medium and multimedia device in which it is used.

State of the art

When encoding or decoding an audio signal, it is required to efficiently use a limited number of bits to restore an audio signal having the best sound quality in a range of a limited number of bits. In particular, at a low transmission speed, it is required that the method of encoding and decoding an audio signal evenly distributes the bits into spectral components important for perception, instead of concentrating the bits in a particular frequency domain.

In particular, at a low transmission rate, in cases where encoding is performed using the bits allocated to each frequency range, for example, a subband, a spectral dip may occur due to the frequency component, which is not encoded due to the insufficient number of bits, thereby leading to degradation sound quality.

SUMMARY OF THE INVENTION

Technical challenge

An aspect is to provide a method and apparatus for efficiently distributing bits in a frequency domain important for perception based on subbands, an audio encoding method and apparatus, an audio decoding method and apparatus, a recording medium, and a multimedia device in which it is used.

An aspect is to provide a method and apparatus for efficiently distributing bits in a frequency region important for perception, with low complexity based on subbands, an audio encoding method and apparatus, an audio decoding method and apparatus, a recording medium, and a multimedia device in which it is used.

The solution of the problem

In accordance with one aspect of one or more exemplary embodiments, a bit allocation method is provided, including: determining a distributed number of bits in decimal units based on each frequency band such that a Signal-to-Noise Ratio (SNR) of a spectrum available in a given frequency range, is maximized within the range of the allowable number of bits for a particular frame; and adjusting the allocated number of bits based on each frequency range.

In accordance with another aspect of one or more exemplary embodiments, there is provided a bit distribution device including: a conversion unit that converts an audio signal in the time domain to a spectrum of audio frequencies in the frequency domain; and a bit allocation unit, which estimates the allowable number of bits in decimal point units by using a masking threshold based on frequency ranges included in a particular frame in the audio frequency spectrum, estimates the distributed number of bits in decimal point units by using spectral energy and adjusts the distributed number bits so that it does not exceed the allowable number of bits.

In accordance with another aspect of one or more exemplary embodiments, an audio encoding device is provided, including: a conversion unit that converts an audio signal in the time domain to a spectrum of audio frequencies in the frequency domain; a bit allocation unit that determines the number of bits to be distributed in units of decimal point based on each frequency range so that the signal-to-noise ratio (SNR) of the spectrum available in a given frequency range is maximized within the range of the allowable number of bits for a particular frame spectrum of sound frequencies, and adjusts the distributed number of bits determined on the basis of each frequency range; and a coding unit that encodes a spectrum of audio frequencies by using the number of bits corrected based on each frequency range and spectral energy.

In accordance with another aspect of one or more exemplary embodiments, an audio decoding apparatus is provided, including: a conversion unit that converts an audio signal in the time domain to a spectrum of audio frequencies in the frequency domain; a bit allocation unit that determines the number of bits to be distributed in units of decimal point based on each frequency range so that the signal-to-noise ratio (SNR) of the spectrum available in a given frequency range is maximized within the range of the allowable number of bits for a particular frame spectrum of sound frequencies, and adjusts the distributed number of bits determined on the basis of each frequency range; and a coding unit that encodes a spectrum of audio frequencies by using the number of bits corrected based on each frequency range and spectral energy.

In accordance with yet another aspect of one or more exemplary embodiments, an audio decoding apparatus is provided, including: a bit allocation unit that estimates a valid number of bits in decimal units by using a masking threshold based on frequency ranges included in a particular frame, estimates the distributed number of bits in decimal units by using spectral energy and adjusts the distributed number of bits so that it does not exceed lo allowable number of bits; a decoding unit that decodes the audio frequency spectrum included in the bitstream by using the number of bits corrected based on each frequency range and spectral energy; and an inverse transform unit that converts the decoded spectrum of the audio frequencies into an audio signal in the time domain.

Brief Description of the Drawings

The foregoing and other embodiments will become more apparent through a detailed description of their exemplary embodiments with reference to the accompanying drawings, in which:

FIG. 1 is a block diagram of an audio encoding apparatus in accordance with an exemplary embodiment;

FIG. 2 is a block diagram of a bit allocation unit in the audio encoding apparatus of FIG. 1 in accordance with an exemplary embodiment;

FIG. 3 is a block diagram of a bit allocation unit in the audio encoding apparatus of FIG. 1 in accordance with another exemplary embodiment;

FIG. 4 is a block diagram of a bit allocation unit in the audio encoding apparatus of FIG. 1 in accordance with another exemplary embodiment;

FIG. 5 is a block diagram of an encoding unit in the audio encoding device of FIG. 1 in accordance with an exemplary embodiment;

FIG. 6 is a block diagram of an audio encoding apparatus in accordance with yet another exemplary embodiment;

FIG. 7 is a block diagram of an audio decoding apparatus in accordance with an exemplary embodiment;

FIG. 8 is a block diagram of a bit allocation unit in the audio decoding apparatus of FIG. 7 in accordance with an exemplary embodiment;

FIG. 9 is a block diagram of a decoding unit in the audio decoding apparatus of FIG. 7 in accordance with an exemplary embodiment;

FIG. 10 is a block diagram of a decoding unit in the audio decoding apparatus of FIG. 7 in accordance with another exemplary embodiment;

FIG. 11 is a block diagram of a decoding unit in the audio decoding apparatus of FIG. 7 in accordance with another exemplary embodiment;

FIG. 12 is a block diagram of an audio decoding apparatus in accordance with another exemplary embodiment;

FIG. 13 is a block diagram of an audio decoding apparatus in accordance with another exemplary embodiment;

FIG. 14 is a structural diagram illustrating a method for allocating bits in accordance with another exemplary embodiment;

FIG. 15 is a structural diagram illustrating a method for allocating bits in accordance with another exemplary embodiment;

FIG. 16 is a structural diagram illustrating a method for allocating bits in accordance with another exemplary embodiment;

FIG. 17 is a structural diagram illustrating a method for allocating bits in accordance with another exemplary embodiment;

FIG. 18 is a block diagram of a multimedia device comprising an encoding module in accordance with an exemplary embodiment;

FIG. 19 is a block diagram of a multimedia device comprising a decoding module in accordance with an exemplary embodiment;

FIG. 20 is a block diagram of a multimedia device comprising an encoding module and a decoding module, in accordance with an exemplary embodiment.

An embodiment of the invention

The present idea of the invention may allow various kinds of changes or modifications and various changes in form, and the specific examples of embodiments will be illustrated and described in detail in the drawings. However, it should be understood that specific exemplary embodiments of the invention do not limit the present idea of the invention to a specific description form, but include any modified, equivalent, or substituted form within the spirit and technical scope of the present idea of the invention. In the following description, well-known functions or constructions are not described in detail since they may complicate the understanding of the invention due to unnecessary details.

Although terms such as “first” and “second” may be used to describe various elements, elements cannot be limited to these terms. These terms can be used to distinguish some element from another element.

The terminology used in this application is used only to describe specific exemplary embodiments and is not intended to limit the present idea of the invention. Although the general terms that are currently used most widely are selected as terms used in the present idea of the invention based on the functions in the present idea of the invention, they can vary in accordance with the intention of specialists, judicial precedents or the advent of new technology. In addition, in some cases, terms specially selected by the applicant may be used, in which case the meaning of the terms will be given in the corresponding description of the invention. In this regard, in the entire present idea of the invention, the terms used in this idea of the invention should not be determined by simple names of terms, but by the meaning of the terms and meaning.

An expression in the singular includes the expression in the plural except in those cases where they are clearly different from each other in some context. It should be understood that in this application, terms such as “include” and “have” are used to indicate the presence of an implemented attribute, number, stage, operation, element, part or combination thereof without exception in advance the possibility of the presence or addition of one or more other signs, numbers, steps, operations, elements, parts or their combination.

Hereinafter, the idea of the invention will be described more fully with reference to the accompanying drawings, in which exemplary embodiments are shown. The same symbols in the drawings indicate the same elements, and therefore, their re-description will not be given.

Expressions used herein, such as “at least one of,” if preceded by a list of items, modify the entire list of items and do not change individual items in the list.

FIG. 1 is a block diagram of an audio encoding apparatus 100 in accordance with an exemplary embodiment.

The audio encoding apparatus 100 of FIG. 1 may comprise a transform unit 130, a bit allocation unit 150, an encoding unit 170, and a multiplexing unit 190. The components of the audio encoding device 100 may be embedded in at least one module and implemented using at least one processor (e.g., a central processing unit (CPU)). In this case, audio can mean an audio signal, a speech signal, or a signal obtained by synthesizing them, but hereinafter, for convenience of description of audio, as a rule, it means an audio signal.

In accordance with FIG. 1, a transform unit 130 can generate a spectrum of audio frequencies by converting an audio signal in the time domain to an audio signal in the frequency domain. Conversion from the time domain to the frequency domain can be performed using various well-known methods, such as Discrete Cosine Transformation (DCT).

The bit allocation unit 150 may determine a masking threshold obtained by using spectral energy or a psychoacoustic model with respect to the spectrum of sound frequencies and the number of bits allocated based on each subband by using spectral energy. In this case, the subband is a block of grouped samples of the spectrum of sound frequencies and can have a constant or variable length due to the correspondence to the threshold range. In cases where the subbands have a variable length, the subbands can be determined so that the number of samples from the initial sample to the last sample included in each subband is gradually increased per frame. In this case, the number of subbands or the number of samples included in each subframe can be determined in advance. According to another embodiment, after one frame is divided by a predetermined number of subbands having a constant length, the constant length may be adjusted in accordance with the distribution of spectral coefficients. The distribution of spectral coefficients can be determined using an indicator of spectral non-uniformity, the difference between the maximum value and the minimum value or the differential value of the maximum value.

According to an exemplary embodiment, the bit allocation unit 150 can estimate the allowable number of bits by using the Norm value obtained from each subband, i.e., average spectral energy, allocate bits based on the average spectral energy and limit the number of bits distributed in this way so that it does not exceed the allowable number of bits.

According to an exemplary embodiment, the bit allocation unit 150 may estimate the allowable number of bits by using a psychoacoustic model based on each subband, distribute the bits based on the average spectral energy, and limit the number of bits allocated so that it does not exceed the allowable number of bits.

The encoding unit 170 may generate information regarding the encoded spectrum by quantizing the audio frequency spectrum and losslessly encoding it based on the distributed number of bits finally determined based on each subband.

The multiplexing unit 190 generates a bitstream by multiplexing the encoded Norm value output from the bit allocation unit 150 and information related to the encoded spectrum output from the encoding unit 170.

The audio encoding device 100 may generate a noise level for an optional subband and output this noise level to an audio decoding device (700 in FIG. 7, 1200 in FIG. 12 or 1300 in FIG. 13).

FIG. 2 is a block diagram of a bit allocation unit 200 corresponding to a bit allocation unit 150 in the audio encoding apparatus 100 in FIG. 1, in accordance with an exemplary embodiment.

The bit allocation unit 200 in FIG. 2 may comprise a Norm estimation block 210, a Norm encoder 230, and a bit estimation and allocation block 250. The components of the bit allocation unit 200 may be embedded in at least one module and implemented using at least one processor.

In accordance with FIG. 2, the norm estimation unit 210 may obtain a norm value corresponding to the average spectral energy based on each subband. For example, the Norm value can be calculated using Equation 1 used in ITU-T G.719, but is not limited to it.

Mat. FIG. one

[Mat. one]

In Equation 1, when there are P subbands or sub-sectors in one frame, N (P) is the Norm of the p-th sub-band or subsector, L _p is the length of the p-th sub-band or subsector, i.e. the number of samples or spectral coefficients, s _p and e _p mean the initial sample and the last sample of the p-th subband, respectively, and y (k) means the sample size or spectral coefficient (i.e. energy).

The Norm value obtained on the basis of each subband may be output to the coding unit (170 in FIG. 1).

The encoder 230 Norms can quantize and encode losslessly the magnitude of the Norm obtained on the basis of each subband. The Norm value quantized on the basis of each subband, or the Norm value obtained by dequantizing the quantized Norm value, can be output to the bit estimation and allocation unit 250. The Norm value quantized and lossless encoded based on each subband can be output to the multiplexing unit (190 in FIG. 1).

Block 250 evaluation and allocation of bits can evaluate and distribute the required number of bits by using the value of the Norm. Preferably, the dequantified Norm value may be used in such a way that the encoding part and the decoding part can use the same process of estimating and allocating bits. In this case, the Norm value adjusted for the masking effect can be used. For example, the Norm value can be adjusted using the psycho-acoustic weighing used in ITU-T G.719, as in Equation 2, but is not limited to it.

Mat. FIG. 2

[Mat. 2]

In Equation 2

means the indicator of the quantized value of the Norm of the r-th sub-range,

means the indicator of the adjusted value of the Norm of the r-th sub-range, and

WSpe (p)

means the offset spectrum for adjusting the rate.

The bit estimator and bit allocation unit 250 may calculate a masking threshold by using a Norm value based on each subband and estimate the number of bits required for perception by using a masking threshold. For this purpose, the Norm value obtained on the basis of each subband can equally be represented as spectral energy in units of dB, as shown in Equation 3.

Mat. FIG. 3

[Mat. 3]

As a method of obtaining a masking threshold, various well-known methods can be used. That is, the masking threshold is a value corresponding to the minimum perceptible distortion (JND), while when the quantization noise is below the masking threshold, perceptual noise cannot be perceived. Thus, the minimum number of bits required so that perceptual noise is not perceived can be calculated using a masking threshold. For example, the Signal-to-Mask Ratio (SMR) can be calculated by using the ratio of the Norm value to the masking threshold based on each subband, and the number of bits satisfying the masking threshold can be estimated by using the 6.025 dB ratio

1 bit relative to the calculated SMR. Although the estimated number of bits is the minimum number of bits required so that perceptual noise is not perceived, since from the point of view of compression there is no need to use the number of bits that exceeds the calculated one, the estimated number of bits can be considered as the maximum number of bits allowed based on each subband (hereinafter referred to as the allowable number of bits). The permissible number of bits of each subband may be represented in units of decimal point.

The bit estimator and bit allocation unit 250 may perform bit allocation in decimal point units by using a Norm value based on each subband. In this case, the bits are sequentially allocated from a subband having a higher Norm value than the others, and it can be adjusted so that more bits are allocated to a perceptual subband by weighting in accordance with the importance for perception of each subband with respect to the Norm value based on each subband. Importance for perception can be determined, for example, by psychoacoustic weighing, as in ITU-T G.719.

The bit estimator and bit allocation unit 250 may sequentially distribute the bits into samples from a subband having a higher Norm value than others. In other words, in the first place, the bits per sample are allocated for a subband having a maximum Norm value, while the priority of a sub range having a maximum Norm value is changed by decreasing the Subrange norm by a predetermined unit so that the bits are allocated to a different sub range. This process is cyclically performed until the total number of B bits allowed in a particular frame is explicitly allocated.

The bit evaluation and allocation unit 250 may finally determine the distributed number of bits by limiting the distributed number of bits so that it does not exceed the estimated number of bits, i.e. allowable number of bits for each subband. For all subbands, the distributed number of bits is compared with the estimated number of bits, and if the distributed number of bits is greater than the estimated number of bits, the distributed number of bits is limited by the estimated number of bits. If the distributed number of bits of all subbands in a particular frame, which is obtained by limiting the number of bits, is less than the total number of B bits allowed in a particular frame, the number of bits corresponding to the difference can be evenly distributed over all subbands or unevenly distributed in accordance with importance for perception .

Since the number of bits allocated to each subband can be determined in units of decimal point and limited by the allowable number of bits, the total number of bits of a particular frame can be allocated efficiently.

According to an exemplary embodiment, a detailed method for estimating and distributing the number of bits required for each subband is as follows. According to this method, since the number of bits allocated to each subband can be determined immediately without repeating several times, the complexity can be reduced.

For example, a solution that can optimize the quantization distortion and the number of bits allocated to each subband can be obtained by applying the Lagrange function represented by Equation 4.

Mat. FIG. four

[Mat. four]

In Equation 4, L stands for the Lagrange function, D stands for quantization distortion, B stands for the total number of bits allowed in a particular frame, N _b stands for the number of samples of the bth subband, and L _b stands for the number of bits allowed in the bth subband. That is, N _b L _b denotes the number of bits allocated to the bth subband.

λ

denotes the Lagrange multiplier, which is the optimization coefficient.

By using Equation 4, L _b can be determined to minimize the difference between the total number of bits allocated to the subbands within a particular frame and the allowable number of bits for a specific frame based on quantization distortion.

The quantization distortion D can be determined using Equation 5.

Mat. FIG. 5

[Mat. 5]

In equation 5

means the input spectrum, and

means decoded spectrum. That is, the quantization distortion D can be defined as the mean square error (MSE) with respect to the input spectrum

and decoded spectrum

in an arbitrary frame.

The denominator in Equation 5 is a constant determined by the specific input spectrum, and therefore, since the denominator in Equation 5 does not affect optimization, Equation 7 can be simplified using Equation 6.

Mat. FIG. 6

[Mat. 6]

Norm Value

,

,

which is the average spectral energy of the bth subband with respect to the input spectrum

,

,

can be determined using Equation 7, the norm value

,

,

quantized on a logarithmic scale can be determined using Equation 8, and the dequantized norm value

can be determined using Equation 9.

Mat. FIG. 7

[Mat. 7]

Mat. FIG. 8

[Mat. 8]

Mat. FIG. 9

[Mat. 9]

In Equation 7, s _b and e _b denote the initial sample and the last sample of the bth subband, respectively.

The normalized spectrum y _{i is} generated by dividing the input spectrum

,

,

dequantized

,

,

as in Equation 10, and the decoded spectrum

generated by multiplying the restored normalized spectrum

dequantized

,

,

as in Equation 11.

Mat. FIG. 10

[Mat. 10]

Mat. FIG. eleven

[Mat. eleven]

The quantization distortion term can be modified using Equation 12 by using Equations 9-11.

Mat. FIG. 12

[Mat. 12]

Typically, from the relationship between quantization distortion and the distributed number of bits, it is determined that the Signal to Noise Ratio (SNR) is increased by 6.02 dB whenever 1 bit is added to the sample, and by using this quantization distortion of the normalized spectrum can be described by Equation 13.

Mat. FIG. 13

[Mat. 13]

In the case of real audio coding, Equation 14 can be determined by applying the C value on a scale in dB, which can vary according to the characteristics of the signal without fixing the ratio of 1 bit / sample

6.025 dB

Mat. FIG. fourteen

[Mat. fourteen]

In Equation 14, in cases where C is 2, 1 bit / sample corresponds to 6.02 dB, and when C is 3, 1 bit / sample corresponds to 9.03 dB.

Thus, Equation 6 can be represented by Equation 15 by Equations 12 and 14.

Mat. FIG. fifteen

[Mat. fifteen]

To obtain the optimal L _b and Λ from Equation 15, a partial differential is satisfied for L _b and Λ, as in Equation 16.

Mat. FIG. 16

[Mat. 16]

When ordering the terms of Equation 16, L _b can be represented by Equation 17.

Mat. FIG. 17

[Mat. 17]

By using Equation 17, the allocated number of L _b bits per sample of each subband that can maximize the SNR of the input spectrum can be estimated in the range of the total number of B bits allowed in a particular frame.

A distributed number of bits based on each subband, which is determined by the bit estimator and bit allocation unit 250, may be provided to a coding unit (170 in FIG. 1).

FIG. 3 is a block diagram of a bit allocation unit 300 corresponding to a bit allocation unit 150 in the audio encoding apparatus 100 in FIG. 1, in accordance with another exemplary embodiment.

The bit allocation unit 300 in FIG. 3 may include a psychoacoustic model 310, a block 330 for estimating and distributing bits, a block for estimating a scale factor 350, and a scale factor encoder 370. The components of the bit allocation unit 300 may be embedded in at least one module and implemented using at least one processor.

In accordance with FIG. 3, the psychoacoustic model 310 can obtain a masking threshold for each subband by receiving a spectrum of audio frequencies from a transform unit (130 in FIG. 1).

Block 330 evaluation and distribution of bits can estimate the number of bits required for perception by using a masking threshold based on each subband. That is, the SMR can be calculated based on each subband, and the number of bits satisfying the masking threshold can be estimated using the ratio of 6.025 dB

1 bit relative to the calculated SMR. Although the estimated number of bits is the minimum number of bits required so that perceptual noise is not perceived, since from the point of view of compression there is no need to use the number of bits that exceeds the calculated one, the estimated number of bits can be considered as the maximum number of bits allowed based on each subband (hereinafter referred to as the allowable number of bits). The permissible number of bits of each subband may be represented in units of decimal point.

Block 330 estimates and distribution of bits can perform the distribution of bits in units of decimal point by using spectral energy based on each subband. In this case, for example, a bit allocation method using Equations 7-20 can be used.

Block 330 evaluation and allocation of bits compares the distributed number of bits with the estimated number of bits for all subbands, and if the distributed number of bits is greater than the estimated number of bits, the distributed number of bits is limited by the estimated number of bits. If the distributed number of bits of all subbands in a particular frame, which is obtained by limiting the number of bits, is less than the total number of B bits allowed in a particular frame, the number of bits corresponding to the difference can be evenly distributed over all subbands or unevenly distributed in accordance with importance for perception .

The scale factor estimator 350 may estimate the scale factor by using a distributed number of bits finally determined based on each subband. A scale factor estimated based on each subband may be provided to a coding unit (170 in FIG. 1).

A scale factor encoder 370 can quantize and losslessly encode a scale factor estimated based on each subband. A scale factor encoded based on each subband may be provided to the multiplexing unit (190 in FIG. 1).

FIG. 4 is a block diagram of a bit allocation unit 400 corresponding to a bit allocation unit 150 in the audio encoding apparatus 100 in FIG. 1, in accordance with another exemplary embodiment.

The bit allocation unit 400 of FIG. 4 may comprise a Norm estimator 410, a bit estimator and distributor 430, a scale factor estimator 450, and a scale factor encoder 470. The components of the bit allocation unit 400 may be embedded in at least one module and implemented using at least one processor.

In accordance with FIG. 4, the norm estimation unit 410 may obtain a norm value corresponding to the average spectral energy based on each subband.

The bit estimator and bit allocation unit 430 may obtain a masking threshold by using spectral energy based on each subband and estimate the number of bits required for perception, i.e. allowable number of bits by using a masking threshold.

Block 430 evaluation and distribution of bits can perform the distribution of bits in units of decimal point by using spectral energy based on each subband. In this case, for example, a bit allocation method using Equations 7-20 can be used.

The bit estimation and allocation unit 430 compares the distributed number of bits with the estimated number of bits for all subbands, and if the distributed number of bits is greater than the estimated number of bits, the distributed number of bits is limited by the estimated number of bits. If the distributed number of bits of all subbands in a particular frame, which is obtained by limiting the number of bits, is less than the total number of B bits allowed in a particular frame, the number of bits corresponding to the difference can be evenly distributed over all subbands or unevenly distributed in accordance with importance for perception .

The scale factor estimator 450 may estimate the scale factor by using a distributable number of bits finally determined based on each subband. A scale factor estimated based on each subband may be provided to a coding unit (170 in FIG. 1).

A scale factor encoder 470 can quantize and code losslessly a scale factor estimated based on each subband. A scale factor encoded based on each subband may be provided to the multiplexing unit (190 in FIG. 1).

FIG. 5 is a block diagram of an encoding unit 500 corresponding to an encoding unit 170 in the audio encoding device 100 in FIG. 1, in accordance with an exemplary embodiment.

The coding unit 500 of FIG. 5 may comprise a spectrum rationing unit 510 and a spectrum encoder 530. The components of the coding unit 500 may be embedded in at least one module and implemented using at least one processor.

In accordance with FIG. 5, the spectrum normalization unit 510 can normalize the spectrum by using the Norm value output from the bit allocation unit (150 in FIG. 1).

Spectrum encoder 530 can quantize a normalized spectrum by using the distributed number of bits of each subband and without lossy encode the quantization result. For example, factor spectral coding can be used for spectral coding, but it is not limited to this. In accordance with factorial pulse coding, information such as the position of the pulse, the amplitude of the pulse, and the sign of the pulse can be represented in factor form within the range of the distributed number of bits.

Information related to the spectrum encoded by the spectrum encoder 530 may be provided to the multiplexing unit (190 in FIG. 1).

FIG. 6 is a block diagram of an audio encoding apparatus 600 in accordance with another exemplary embodiment.

The audio encoding device 600 of FIG. 6 may include a transient detection unit 610, a conversion unit 630, a bit allocation unit 650, an encoding unit 670, and a multiplexing unit 690. The components of the audio encoding unit 600 may be embedded in at least one module and implemented using at least one processor. Since there is a difference in that when comparing the audio encoding apparatus 600 in FIG. 6 with the audio encoding apparatus 100 in FIG. 1, the audio encoding apparatus 600 of FIG. 6 further comprises a transient detection unit 610, a detailed description of common components is not provided in this case.

In accordance with FIG. 6, a transient detection unit 610 may detect an interval indicating a transient response by analyzing an audio signal. Various well-known methods can be used to detect the transient interval. Transient signaling information provided from the transient detection unit 610 may be included in the bitstream using the multiplexing unit 690.

Conversion unit 630 may determine the size of the window used for conversion in accordance with the result of detecting a transient interval and perform the conversion from the time domain to the frequency domain based on the determined window size. For example, a short window may be applied to a subband from which a transient interval is detected, and a long window may be applied to a subband from which a transient interval is not detected.

A bit allocation unit 650 may be implemented using one of the bit allocation units 200, 300, and 400 in FIG. 2, 3 and 4, respectively.

Block 670 encoding may determine the size of the window used for encoding, in accordance with the result of detecting a transient interval.

An audio encoding device 600 may generate a noise level for an optional subband and output this noise level to an audio decoding device (700 in FIG. 7, 1200 in FIG. 12 or 1300 in FIG. 13).

FIG. 7 is a block diagram of an audio decoding apparatus 700 in accordance with an exemplary embodiment.

The audio decoding apparatus 700 of FIG. 7 may comprise a demultiplexing unit 710, a bit allocation unit 730, a decoding unit 750, and an inverse transform unit 770. The components of an audio decoding device may be embedded in at least one module and implemented using at least one processor.

In accordance with FIG. 7, a demultiplexing unit 710 may demultiplex a bitstream to extract a quantized and lossless encoded Norm value and information related to the encoded spectrum.

The bit allocation unit 730 may obtain a dequantified Norm value from a quantized and lossless encoded Norm value based on each subband and determine a distributed number of bits by using a dequantized Norm value. The bit allocation unit 730 may operate essentially the same as the bit allocation unit 150 or 650 of the audio encoding apparatus 100 or 600. In cases where the Norm value is adjusted using psychoacoustic weighing in the audio encoding device 100 or 600, the dequantized Norm value can be adjusted using the audio encoding device 700 in a similar manner.

The decoding unit 750 can losslessly encode and dequantize the encoded spectrum by using information related to the encoded spectrum and output from the demultiplexing unit 710. For example, pulse decoding may be used to decode the spectrum.

The inverse transform unit 770 may generate the reconstructed audio signal by converting the decoded spectrum to the time domain.

FIG. 8 is a block diagram of a bit allocation unit 800 in the audio decoding apparatus 700 of FIG. 7 in accordance with an exemplary embodiment.

The bit allocation unit 800 in FIG. 8 may comprise a Norm decoder 810 and a bit estimation and allocation unit 830. The components of the bit allocation unit 800 may be integrated into at least one module and implemented by at least one processor.

In accordance with FIG. 8, a Norm decoder 810 can obtain a dequantized Norm value from a quantized and lossless encoded Norm value output from a demultiplexing unit (710 in FIG. 7).

An estimator and bit allocation unit 830 may determine the distributable number of bits by using a dequantified Norm value. Namely, the block 830 evaluation and distribution of bits can obtain a masking threshold by using spectral energy, i.e. Norm values based on each subband and estimate the number of bits required for perception, i.e., the allowable number of bits by using a masking threshold.

Block 830 evaluation and distribution of bits can perform the distribution of bits in units of decimal point by using spectral energy, i.e. Norm values based on each subrange. In this case, for example, a bit allocation method using Equations 7-20 can be used.

Block 830 evaluation and allocation of bits compares the distributed number of bits with the estimated number of bits for all subbands, and if the distributed number of bits is greater than the estimated number of bits, the distributed number of bits is limited by the estimated number of bits. If the distributed number of bits of all subbands in a particular frame, which is obtained by limiting the number of bits, is less than the total number of B bits allowed in a particular frame, the number of bits corresponding to the difference can be evenly distributed over all subbands or unevenly distributed in accordance with importance for perception .

FIG. 9 is a block diagram of a decoding unit 900 corresponding to a decoding unit 750 in the audio decoding apparatus 700 of FIG. 7, in accordance with an exemplary embodiment.

The decoding unit 900 of FIG. 9 may include a spectrum decoder 910 and an envelope shaping unit 930. The components of the decoding unit 900 may be embedded in at least one module and implemented using at least one processor.

In accordance with FIG. 9, the spectrum decoder 910 can losslessly decode and quantize the encoded spectrum by using information related to the encoded spectrum from the demultiplexing unit (710 in FIG. 7) and the distributed number of bits output from the bit allocation unit (730 in FIG. 7) . The decoded spectrum from spectrum decoder 910 is a normalized spectrum.

Envelope shaping unit 930 can reconstruct the spectrum before normalization by performing envelope shaping from the normalized spectrum output from the spectrum decoder 910 by using the dequantized Norm value output from the bit allocation unit (730 in FIG. 7).

FIG. 10 is a block diagram of a decoding unit 1000 corresponding to a decoding unit 750 in the audio decoding apparatus 700 in FIG. 7 in accordance with another exemplary embodiment.

The decoding unit 1000 of FIG. 10 may include a spectrum decoder 1010, an envelope generating unit 1030, and a spectrum filling unit 1050. The components of the decoding unit 1000 may be embedded in at least one module and implemented using at least one processor.

In accordance with FIG. 10, the spectrum decoder 1010 can losslessly decode and quantize the encoded spectrum by using information related to the encoded spectrum from the demultiplexing unit (710 in FIG. 7) and the distributed number of bits output from the bit allocation unit (730 in FIG. 7) . The decoded spectrum from spectrum decoder 1010 is a normalized spectrum.

The envelope generating unit 1030 can reconstruct the spectrum before normalization by performing envelope formation from the normalized spectrum output from the spectrum decoder 1010 by using the dequantized Norm value output from the bit allocation unit (730 in FIG. 7).

In cases where the spectrum outputted from the envelope generating unit 1030 has a subband containing the element dequantized to 0, the spectrum filling unit 1050 can fill the noise component in the element dequantized to 0 in this subband. According to an exemplary embodiment, the noise component may be randomly generated or generated by copying a subband spectrum dequantized to a value not equal to 0 that is adjacent to a subband containing an element dequantized to 0, or a subband spectrum dequantized to a value not equal to 0 According to yet another exemplary embodiment, the energy of the noise component can be corrected by generating a noise component for a subband containing an element dequantized to 0, and using the ratio of the energy of the noise component to the dequantized Norm value output from the bit distribution block (730 in Fig. 7), i.e. spectral energy. In accordance with yet another exemplary embodiment, a noise component for a subband containing an element dequantized to 0 may be generated, wherein the average energy of the noise component may be adjusted to 0.

FIG. 11 is a block diagram of a decoding unit 1100 corresponding to a decoding unit 750 in the audio decoding apparatus 700 of FIG. 7, in accordance with another exemplary embodiment.

The decoding unit 1100 of FIG. 11 may include a spectrum decoder 1110, a spectrum filling unit 1130, and an envelope shaping unit 1150. The components of the decoding unit 1100 may be embedded in at least one module and implemented using at least one processor. Since there is a difference in that when comparing the decoding unit 1100 in FIG. 11 with decoding apparatus 1000 in FIG. 10, the layout of the spectrum filling unit 1130 and the envelope forming unit 1150 are different, a detailed description of the common components is not given in this case.

In accordance with FIG. 11 in cases where the normalized spectrum output from the spectrum decoder 1110 has a subband containing the element de-quantized to 0, the spectrum filling unit 1130 may fill the noise component in the element de-quantized to 0 in this sub-range. In this case, various noise filling methods applicable to the noise filling block 1050 of FIG. 10. Preferably, a noise component can be generated for the subband containing the element dequantized to 0, while the average energy of the noise component can be adjusted to 1.

Envelope shaping unit 1150 can reconstruct the spectrum before normalization for a spectrum containing a subband in which the noise component is populated by using the dequantized Norm value output from the bit allocation unit (730 in FIG. 7).

FIG. 12 is a block diagram of an audio decoding apparatus 1200 in accordance with another exemplary embodiment.

The audio decoding apparatus 1200 in FIG. 12 may comprise a demultiplexing unit 1210, a scale factor decoder 1230, a spectrum decoder 1250, and an inverse transform unit 1270. The components of the audio decoding apparatus 1200 may be embedded in at least one module and implemented using at least one processor.

In accordance with FIG. 12, a demultiplexing unit 1210 may demultiplex a bitstream to extract a quantized and losslessly encoded scale factor and information related to the encoded spectrum.

A scale factor decoder 1230 may losslessly encode and quantize a quantized and lossless encoded scale factor based on each subband.

The spectrum decoder 1250 can losslessly decode and dequantize the encoded spectrum by using information related to the encoded spectrum and the dequantized scale factor provided from the demultiplexing unit 1210. The spectrum decoding unit 1250 may contain the same components as the decoding unit 1000 in FIG. 10.

The inverse transform unit 1270 may generate the reconstructed audio signal by converting the spectrum decoded by the spectrum decoder 1250 to the time domain.

FIG. 13 is a block diagram of an audio decoding apparatus 1300 in accordance with another exemplary embodiment.

The audio decoding apparatus 1300 of FIG. 13 may comprise a demultiplexing unit 1310, a bit allocation unit 1330, a decoding unit 1350, and an inverse transform unit 1370. The components of the audio decoding apparatus 1300 may be embedded in at least one module and implemented using at least one processor.

Since there is a difference in that when comparing the audio decoding apparatus 1300 in FIG. 13 with the audio decoding apparatus 700 of FIG. 7, transient signaling information is provided to a decoding unit 1350 and an inverse transforming unit 1370, a detailed description of common components is not given in this case.

In accordance with FIG. 13, decoding unit 1350 may decode the spectrum by using information related to the encoded spectrum provided from the multiplexing unit 1310. In this case, the window size may vary in accordance with the signaling information about the transient.

The inverse transform unit 1370 may generate the reconstructed audio signal by converting the decoded spectrum to the time domain. In this case, the window size may vary in accordance with the signaling information about the transient.

FIG. 14 is a flowchart illustrating a bit allocation method in accordance with yet another exemplary embodiment.

In accordance with FIG. 14, in operation 1410, the spectral energy of each subband is extracted. Spectral energy may be a norm value.

In operation 1420, a masking threshold is extracted by using spectral energy based on each subband.

In operation 1430, the allowable number of bits in decimal point units is estimated by using a masking threshold based on each subband.

In step 1440, bits are allocated in decimal units based on spectral energy based on each subband.

In operation 1450, the allowable number of bits is compared with a distributed number of bits based on each subband.

In step 1460, if, as a result of the comparison in step 1450, the distributed number of bits is greater than the allowable number of bits for a particular subband, the distributed number of bits is limited by the allowable number of bits.

In step 1470, if, as a result of the comparison in step 1450, the distributed number of bits is not greater than the allowable number of bits for a particular subband, the distributed number of bits is used as it is, or the final distributed number of bits is determined for each subband by using the allocated number bits limited to performing operation 1460.

Although not shown, if the sum of the distributed number of bits determined in step 1470 for all subbands in a particular frame is greater than or less than the total number of bits allowed in a particular frame, the number of bits corresponding to the difference can be uniformly distributed across all subbands or unevenly distributed according to importance for perception.

FIG. 15 is a flowchart illustrating a method for allocating bits in accordance with another exemplary embodiment.

In accordance with FIG. 15, in operation 1500, a dequantized Norm value of each subband is extracted.

In operation 1510, a masking threshold is retrieved by using a dequantized Norm value based on each subband.

In operation 1520, the SMR is extracted by using a masking threshold based on each subband.

In operation 1530, the allowable number of bits is estimated in units of decimal point by using SMR based on each frequency range.

In step 1540, the bits are allocated in decimal point units based on spectral energy (or the dequantified Norm value) based on each subband.

In operation 1550, the allowable number of bits is compared with a distributed number of bits based on each subband.

In step 1560, if, as a result of the comparison in step 1550, the distributed number of bits is greater than the allowable number of bits for a particular subband, the distributed number of bits is limited by the allowable number of bits.

In step 1570, if, as a result of the comparison in step 1550, the distributed number of bits is not more than the allowable number of bits for a particular subband, the distributed number of bits is used as it is, or the final distributed number of bits is determined for each subband by using the allocated number bits limited to performing operation 1560.

Although not shown, if the sum of the distributed number of bits determined in step 1570 for all subbands in a particular frame is less than or greater than the total number of bits allowed in a particular frame, the number of bits corresponding to the difference can be uniformly distributed across all subbands or unevenly distributed according to perceptual importance.

FIG. 16 is a flowchart illustrating a bit allocation method in accordance with yet another exemplary embodiment.

In accordance with FIG. 16, in operation 1610, initialization is performed. As an example of initialization, when the allocated number of bits for each subband is estimated by using Equation 20, the overall complexity can be reduced by calculating a constant:

for all subbands.

In step 1620, the allocated number of bits for each subband is estimated in units of decimal point by using Equation 17. The distributed number of bits for each subband can be obtained by multiplying the allocated number L _b bits per sample by the number of samples per subband. In cases where the distributed number of L _b bits per sample of each subband is calculated by using Equation 17, L _b may have a value of less than 0. In this case, 0 is allocated to a number L _b having a value of less than 0, as in Equation 18.

Mat. FIG. eighteen

[Mat. eighteen]

As a result, the sum of the distributed number of bits estimated for all subbands included in a particular frame may be greater than the number of B bits allowed in a particular frame.

In step 1630, the sum of the allocated number of bits estimated for all subbands included in a particular frame is compared with the number of B bits allowed in a particular frame.

In step 1640, the bits are redistributed for each subband using Equation 19 until the sum of the allocated number of bits estimated for all the subbands included in a particular frame is the same as the number of B bits allowed in a particular frame.

Mat. FIG. 19

[Mat. 19]

In Equation 19

means the number of bits determined by the (k-1) th repetition, and

means the number of bits determined by the kth repetition. The number of bits determined by each repetition must be at least 0, and accordingly, operation 1640 is performed for all subbands having a number of bits greater than 0.

In step 1650, if, as a result of the comparison in step 1630, the sum of the distributed number of bits estimated for all subbands included in a particular frame is the same as the number of B bits allowed in a specific frame, the distributed number of bits of each the subband is used as it is, or the final allocated number of bits is determined for each subband by using the allocated number of bits of each subband, which is obtained as a result of the redistribution tion during operation 1640.

FIG. 17 is a flowchart illustrating a bit allocation method in accordance with yet another exemplary embodiment.

In accordance with FIG. 17 as in step 1610 of FIG. 16, in operation 1710, initialization is performed. As with operation 1620 of FIG. 16, in step 1720, the allocated number of bits for each subband is estimated in units of decimal point, and when the distributed number of L _b bits per sample for each subband is less than 0, 0 is allocated to the number L _b having a value less than 0, as in Equation 18 .

In step 1730, the minimum number of bits required for each subband is determined in terms of SNR, and the distributed number of bits in step 1720, greater than 0 and less than the minimum number of bits, is adjusted by limiting the distributed number of bits to the minimum number of bits. In this regard, by limiting the distributed number of bits of each subband to the minimum number of bits, the possibility of lowering the sound quality can be reduced. For example, the minimum number of bits required for each subband is defined as the minimum number of bits required for pulse coding in factorized pulse coding. Pulse factor coding represents a signal by using all combinations of a pulse position other than 0, pulse amplitude, and pulse sign. In this case, the random number N of all combinations that can represent momentum can be represented by Equation 20.

Mat. FIG. twenty

[Mat. twenty]

In Equation 20 2 ⁱ means a random number of characters represented by +/- for signals in i non-zero positions.

In Equation 20, F (n, i) can be determined using Equation 21 and means a random number for choosing i non-zero positions for specific n samples, i.e. provisions.

Mat. FIG. 21

[Mat. 21]

In Equation 20, D (m, i) can be represented using Equation 22 and means a random number to represent signals selected at i non-zero positions using m amplitudes.

Mat. FIG. 22

[Mat. 22]

The number of M bits required to represent N combinations can be represented using Equation 23.

Mat. FIG. 23

[Mat. 23]

M = [log ₂ N ]

As a result, the minimum number

the bits required to encode at least 1 pulse for N _b samples in a particular bth subband may be represented by Equation 24.

Mat. FIG. 24

[Mat. 24]

In this case, the number of bits used to transmit the magnitude of the gain required for quantization can be added to the minimum number of bits required by factorial pulse coding, and can vary in accordance with the bit rate. The minimum number of bits required based on each subband may be determined by a larger value from the minimum number of bits required by factorization coding and the number N _{b of} samples of a particular subband, as in Equation 25. For example, the minimum number of bits required based on each subband, can be set to 1 bit per sample.

Mat. FIG. 25

[Mat. 25]

In cases where, in step 1730, the used bits are not enough, since the target bit rate is small, for a range for which the distributed number of bits is greater than 0 and less than the minimum number of bits, the distributed number of bits is deleted and set to 0. In addition, for the subband for which the distributed number of bits is less than in Equation 24, the distributed number of bits can be deleted, and for a subband for which the distributed number of bits is greater than in Equation 24 and less than the minimum The number of bits in Equation 25 may be allocated a minimum number of bits.

In operation 1740, the sum of the allocated number of bits estimated for all subbands in a particular frame is compared with the number of bits allowed in a particular frame.

In step 1750, the bits are redistributed for the subband into which more than the minimum number of bits is allocated, until the sum of the allocated number of bits estimated for all the subbands in a particular frame is the same as the number of bits allowed in a particular frame.

In operation 1760, it is determined whether the allocated number of bits of each subband is changed between the previous repetition and the current repetition to redistribute the bits. If the allocated number of bits of each subband does not change between the previous repetition and the current repetition to redistribute the bits, or until the sum of the distributed number of bits estimated for all subbands in a particular frame becomes the same as the number of bits allowed in a particular frame, operations 1740-1760 are performed.

In step 1770, if, as a result of the determination in step 1760, the allocated number of bits of each subband does not change between the previous repetition and the current repetition to redistribute the bits, the bits are sequentially deleted from the upper subband to the lower subband, and operations 1740-1760 are performed until as long as the number of bits allowed in a particular frame is not acceptable. In addition, if the distributed number of bits is not greater than the minimum number of bits in Equation 25 for all subbands, and the sum of the distributed number of bits is greater than the number of bits allowed in a particular frame, the distributed number of bits can be removed from the high-frequency range to the low-frequency range.

In accordance with the bit allocation methods of FIG. 16 and 17 for distributing bits to each subband after the initial bits are allocated to each subband in order of spectral energy or weighted spectral energy, the number of bits required for each subband can be estimated immediately without repeating the operation of searching for spectral energy or weighted spectral energy in for several times. In addition, by redistributing the bits into each subband until the sum of the allocated number of bits estimated for all subbands in a particular frame becomes the same as the number of bits allowed in a particular frame, an efficient bit allocation is possible. In addition, by ensuring a minimum number of bits in an arbitrary subband, the formation of a spectral dip can be prevented due to the fact that, due to the distribution of a small number of bits, a sufficient number of spectral samples or pulses cannot be encoded.

The methods of FIG. 14-17 may be programmed and may be implemented using at least one processing device, for example, a central processing unit (CPU).

FIG. 18 is a block diagram of a multimedia device comprising an encoding module in accordance with an exemplary embodiment.

In accordance with FIG. 18, multimedia device 1800 may include a communication unit 1810 and an encoding module 1830. In addition, the multimedia device 1800 may further comprise a memory unit 1850 for storing an audio bitstream resulting from encoding in accordance with the use of an audio bitstream. In addition, the multimedia device 1800 may further comprise a microphone 1870. That is, the memory unit 1850 and the microphone 1870 may optionally be included. The multimedia device 1800 may further comprise an arbitrary decoding module (not shown), for example, a decoding module for performing a common decoding function or a decoding module in accordance with an exemplary embodiment. Encoding module 1830 may be implemented using at least one processor, such as a central processor (not shown), by combining with other components (not shown) that are part of the multimedia device 1800 as a whole.

The communication unit 1810 may receive at least one of the audio signal or the encoded bit stream from the outside, or transmit at least one of the reconstructed audio signal or the encoded bit stream obtained by encoding using the encoding module 1830.

The communication unit 1810 is configured to transmit and receive data to and from an external multimedia device using a wireless network such as wireless Internet, wireless intranet, wireless telephone network, wireless Local Area Network (LAN), Wi-Fi, Wi-Fi Direct ( WFD), Third Generation (3G), Fourth Generation (4G), Bluetooth, Infrared Data Technology Association (IrDA), Radio Frequency Identification (RFID), Ultra Wide Bandwidth (UWB), Zigbee, or Near Field Communication (NFC) ), or a wired network such as wired telephone network or wired Internet.

According to an exemplary embodiment, the encoding module 1830 can generate a bitstream by converting the audio signal in the time domain, which is generated by the communication unit 1810 or microphone 1870, into the audio frequency spectrum in the frequency domain, determining the distributed number of bits in decimal units based on frequency ranges so that the SNR of the spectrum available in a given frequency range is maximized within the range of the number of bits allowed in a particular frame of the sound spectrum new frequencies, adjusting the distributed number of bits, determined on the basis of frequency ranges, and coding the spectrum of audio frequencies by using the number of bits, adjusted on the basis of frequency ranges and spectral energy.

According to an exemplary embodiment, the encoding module 1830 can generate a bitstream by converting an audio signal in the time domain, which is generated by the communication unit 1810 or microphone 1870, into an audio frequency spectrum in the frequency domain, estimating the allowable number of bits in decimal points by using masking threshold based on frequency ranges included in a particular frame of the audio frequency spectrum, estimates of the distributed number of bits in decimal point units by using mations spectral energy adjusting the number of bits distributed so that it does not exceed the permissible number of bits, and coding of audio frequency range by using a number of bits corrected based on the frequency bands and spectral energy.

The memory unit 1850 may store the encoded audio stream generated by the encoding module 1830. In addition, the memory unit 1850 may store various programs required for the operation of the multimedia device 1800.

Microphone 1870 may provide an audio signal from a user or external environment to coding module 1830.

FIG. 19 is a block diagram of a multimedia device comprising a decoding module in accordance with an exemplary embodiment.

The multimedia device 1900 of FIG. 19 may comprise a communication unit 1910 and a decoding unit 1930. In addition, in accordance with the use of the reconstructed audio signal obtained as a decoding result, the multimedia device 1900 in FIG. 19 may further comprise a memory unit 1950 for storing the reconstructed audio signal. In addition, the multimedia device 1800 may further comprise a loudspeaker 1970. That is, a memory unit 1950 and a loudspeaker 1970 are optional. The multimedia device 1900 of FIG. 19 may further comprise an encoding module (not shown), for example, an encoding module for performing a general encoding function or an encoding module in accordance with an exemplary embodiment. Decoding module 1930 may be combined with other components (not shown), included in multimedia device 1900, and implemented using at least one processor, such as a central processing unit (CPU).

In accordance with FIG. 19, the communication unit 1910 may receive at least one of the audio signal or the encoded bitstream from the outside, or may transmit at least one of the reconstructed audio signal obtained by decoding by the decoding unit 1930 or the audio bitstream obtained from the encoding. The communication unit 1910 can be implemented essentially similar to the communication unit 1810 in FIG. eighteen.

According to an exemplary embodiment, the decoding module 1930 can generate the reconstructed audio signal by receiving a bit stream generated by the communication unit 1910, determining a distributable number of bits in decimal point units based on frequency ranges such that the SNR of the spectrum in each frequency range, maximized within the range of the allowable number of bits in a particular frame, adjustments to the distributed number of bits determined based on frequency ranges, d encoding the sound spectrum included in the bit stream by use of a number of bits corrected on the basis of frequency bands, and the spectral energy and convert the decoded audio frequency spectrum into an audio signal in the time domain.

According to another exemplary embodiment, the decoding module 1930 can generate a bitstream by receiving a bitstream generated by the communication unit 1910, estimating the allowable number of bits in decimal point units by using a masking threshold based on frequency ranges included in a particular frame, estimating the distributed number of bits in decimal units by using spectral energy, adjusting the distributed number of bits so that it does not exceed the permissible number of bits was obtained, decoding the spectrum of audio frequencies included in the bitstream by using the number of bits, adjusted based on frequency ranges and spectral energy, and converting the decoded spectrum of audio frequencies to an audio signal in the time domain.

The memory unit 1950 may store the reconstructed audio signal generated by the decoding unit 1930. In addition, the memory unit 1950 may store various programs required for operation of the multimedia device 1900.

Loudspeaker 1970 may provide a reconstructed audio signal generated by decoding unit 1930 to an external environment.

FIG. 20 is a block diagram of a multimedia device comprising an encoding module and a decoding module, in accordance with an exemplary embodiment.

The multimedia device 2000 shown in FIG. 20 may include a communication unit 2010, an encoding module 2020, and a decoding module 2030. In addition, the multimedia device 2000 may further comprise a memory unit 2040 for storing an audio bitstream obtained by encoding, or a reconstructed audio signal obtained by decoding, in accordance with the use of an audio bitstream or restored audio signal. In addition, the multimedia device 2000 may further comprise a microphone 2050 and / or a loudspeaker 2060. The encoding module 2020 and the decoding module 2030 may be implemented using at least one processor, for example, a central processing unit (CPU) (not shown) by combining with other components (not shown) included in the multimedia device 2000 as a whole.

Since the components of the multimedia device 2000 shown in FIG. 20 correspond to the components of the multimedia device 1800 of FIG. 18, or components of the multimedia device 1900 of FIG. 19, their detailed description is not given.

Each of the multimedia devices 1800, 1900, and 2000 shown in FIG. 18, 19 and 20 may comprise a voice-only terminal device, such as a telephone or mobile phone, a music or broadcast only device, such as a television or an MP3 player, or a hybrid terminal device from a voice-only terminal and a broadcast only device or transmission, but not limited to. In addition, each of the multimedia devices 1800, 1900, and 2000 can be used as a client, server, or converter located between the client and server.

In cases where the multimedia device 1800, 1900 or 2000 is, for example, a mobile phone, although not shown, the multimedia device 1800, 1900 or 2000 may further comprise a user input unit, such as a keyboard, a display unit for displaying information being processed a user interface or mobile phone; and a processor for controlling the functions of the mobile phone. In addition, the mobile phone may further comprise a camera unit having an imaging function, and at least one component for performing the function required for the mobile phone.

In cases where the multimedia device 1800, 1900 or 2000 is, for example, a television, although not shown, the multimedia device 1800, 1900 or 2000 may further comprise a user input unit, such as a keyboard, a display unit for displaying received broadcast information and processor to control all the functions of the TV. In addition, the television may further comprise at least one component for performing the function of the television.

The methods in accordance with these embodiments may be recorded in the form of computer programs and may be implemented in universal digital computers that execute programs using a computer-readable recording medium. In addition, data structures, program instructions, or data arrays applicable in these exemplary embodiments may be recorded on a computer-readable recording medium in various ways. A computer-readable recording medium is any data storage device capable of storing data that can then be read by a computing system. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs and DVDs, and magneto-optical media such as floppy disks, and hardware devices such as read-only memory ( ROM), random access memory (RAM) and flash memory, in particular, configured to store and execute program instructions. In addition, the computer-readable recording medium may be a transmission medium for transmitting a signal in which a program instruction and data structure are provided. Program instructions may contain machine codes edited by the compiler and high-level language codes executed by a computer using an interpreter.

Despite the fact that the present idea of the invention is depicted and described in detail with reference to its exemplary embodiments, it should be clear to those skilled in the art that various changes in form and detail are possible within the spirit and scope of the present invention as defined by the following claims.

Claims (18)

1. A method for distributing bits, comprising the steps of: estimating the number of bits for each of the multiple subbands in the frame of the input spectrum in the form of fractions taking into account the allowable number of bits for the frame; and redistributing the estimated number of bits in at least one subband having the number of bits greater than zero, until the total number of bits for the frame becomes equal to the allowable number of bits for the frame, wherein the number of allocated bits for the subband is equal to or greater than the predetermined minimum number of bits required for the subband, and wherein the input spectrum has at least one of audio characteristics and speech characteristics. 2. The method of claim 1, wherein the bit estimation is performed based on the spectral energy of each of the plurality of subbands. 3. The method according to claim 1, wherein the redistribution includes limiting the number of distributed bits for the subband when the number of distributed bits for the subband is less than the predetermined minimum number of bits. 4. A computer-readable recording medium containing computer-readable code executed by a processor to perform the method of claim 1. 5. A device for distributing bits, containing: at least one processor configured to: receive an input signal of a time domain; generate a spectrum by converting the input signal of the time domain into the input signal of the frequency domain; estimate the number of bits for each of the multiple subbands in the frame of the specified spectrum in the form of fractions taking into account the allowable number of bits for the frame; and redistribute the estimated number of bits into at least one subband having the number of bits greater than zero, until the total number of bits for the frame becomes equal to the allowable number of bits for the frame, wherein the number of allocated bits for the subband is equal to or greater than the predetermined minimum number of bits required for the subband, and wherein the input signal has at least one of an audio characteristic and a speech characteristic. 6. The device according to claim 5, in which at least one processor is configured to estimate the number of bits for each of the multiple subbands based on the spectral energy of each of the multiple subbands. 7. The device according to claim 5, in which at least one processor is configured to limit the number of distributed bits for a subband when the number of distributed bits for a subband is less than a predetermined minimum number of bits.

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